Utilizing Tech is a weekly podcast focusing on practical applications of various technologies in the modern enterprise. Each season focuses on a specific area of emerging technology, with three…

Utilizing Tech is a weekly podcast focusing on practical applications of various technologies in the modern enterprise. Each season focuses on a specific area of emerging technology, with three…

Utilizing Tech is a weekly podcast focusing on practical applications of various technologies in the modern enterprise. Each season focuses on a specific area of emerging technology, with three…

WekaIO Inc. today announced what it says is its most significant product refresh to date. The distributed big-data management platform provider unveiled a massive overhaul of its flagship software together with the release of its first custom-designed storage hardware that’s built specifically for artificial intelligence inference. The two-pronged announcement saw the company launch WEKA NeuralMesh 6, the latest iteration of its software that’s designed to eliminate the storage and memory bottlenecks holding back AI inference workloads. It’s designed to run on the new WEKApod Nitro, WEKApod Prime and WEKApod Prime Max AI appliances that promise to deliver the perfect combination of capacity and performance for running interference workloads at scale with a reduced footprint and energy consumption. According to WekaIO, it really could not have timed the release of its new software and systems any better. It says enterprise AI is reaching a critical inflection point as more organizations shift away from training AI models to running them in production inference environments. The startup believes that the AI training-focused storage infrastructures of yesterday are quite unsuitable for the long-context reasoning, agentic workflows and retrieval-augmented generation workloads that are now the main focus of most organization’s AI efforts. Simply put, most...

Companies that raised venture capital funding in May included CoreWeave, Scale AI, Sigma and WekaIO.

The next great AI race may be won not on raw compute, but on memory. With shortages exposing hard limits across data centers, AI memory optimization is taking center stage as a way to unlock more tokens, more efficiency and more value from the same infrastructure. What was once a backstage infrastructure concern is now a primary competitive advantage, according to Val Bercovici (pictured, left), chief AI officer of WekaIO Inc. In a proof of concept conducted with Firmus Technologies Pty Ltd, Weka used storage economics to extend memory — preserving context instead of repeatedly reprocessing it on GPUs — to show how organizations could dramatically increase token output without increasing energy consumption. “The results were what we expected, which was [that] you’re able to get — out of the same CapEx and OpEx, the same GPUs and energy cost — 6.5 times more, so 550% more, tokens,” Bercovici said. “It’s as if in a macro scenario, you just created five and a half new data centers out of thin air.” Bercovici and Daniel Kearney (right), chief technology officer of Firmus Technologies Pty Ltd., spoke with theCUBE’s Gemma Allen at the Nvidia GTC AI Conference & Expo, during an exclusive...

Weka's certification for NVIDIA's Blackwell GB200 platform creates a revolutionary data infrastructure that maximizes GPU utilization for AI reasoning workloads.In the rapidly evolving landscape of ar...

WekaIO (WEKA), the AI-native data platform company, today announced that the WEKA Data Platform has been certified as a high-performance data store for NVIDIA Partner Network Cloud Partners. With this certification, NVIDIA Cloud Partners can now lev...

WekaIO (WEKA), the AI-native data platform company, today announced that the WEKA Data Platform has been certified as a high-performance data store for NVIDIA Partner Network Cloud Partners. With this certification, NVIDIA Cloud Partners can now lev...